Economics (Econometrics and Big Data) MSc - 2023/4

Awarding body

University of Surrey

Teaching institute

University of Surrey

Framework

FHEQ Levels 6 and 7

Final award and programme/pathway title

MSc Economics (Econometrics and Big Data)

Subsidiary award(s)

Award	Title
PGDip	Economics (Econometrics and Big Data)
PGCert	Economics (Econometrics and Big Data)

Modes of study

	Route code	Credits and ECTS Credits
Full-time	PLC61017	180 credits and 90 ECTS credits

QAA Subject benchmark statement (if applicable)

Other internal and / or external reference points

N/A

Faculty and Department / School

Faculty of Arts and Social Sciences - Economics

Programme Leader

GARFAGNINI Umberto (Economics)

Date of production/revision of spec

19/04/2024

Educational aims of the programme

Engage the whole learner with a transformative curriculum that promotes advanced knowledge and offers ample opportunity to do, create, develop, and self-reflect
Enhance student employability, resilience and resourcefulness, global and cultural capabilities, sustainability awareness, and digital capabilities (the five pillars of the University of Surrey¿s Curriculum Framework) through a range of appropriate, contemporary, and engaging pedagogical methods
Develop an appreciation of economics, both as an intellectual discipline and as an important contributor to an understanding of the world in ways which are of practical significance, with a focus on the use of econometric techniques applied to big data
Facilitate effective learning and communication within an open, scholarly environment by fostering knowledge discovery and the creation of personal meaning
Promote the capacity for independent study through the completion of an MSc dissertation in econometrics and big data
Prepare students for a range of careers in which advanced quantitative analysis and independent thought, as well as the qualities developed through the application of the curriculum framework, can contribute to self-fulfilment and/or an improvement in social and economic welfare
Enable better performing students completing the programme to progress to postgraduate research in economics and econometrics

Programme learning outcomes

	Attributes Developed	Awards	Ref.
Demonstrate an advanced understanding of the core principles in microeconomics, macroeconomics, and econometrics with a focus on the use of econometric techniques applied to big data	K	PGCert, PGDip, MSc
Show a systematic understanding of the techniques used in contemporary economic research	K	PGDip, MSc
Establish a critical awareness of current and advanced problems and the methodologies that are most common in economics and econometrics	K	PGCert, PGDip, MSc
Evidence understanding of different methodologies and an ability to choose amongst these as required in different settings, with a special reference to big data	C	PGDip, MSc
Combine relevant theory and analytical techniques with insightful data analysis to produce convincing explanations of economic phenomena	C	MSc
Comprehend published economic research papers and integrate the implications of published research in own studies	C	PGDip, MSc
Demonstrate high-level problem-solving skills	P	PGDip, MSc
Select appropriate techniques to evaluate policy interventions	P	PGDip, MSc
Communicate the results of independent research in the form of a dissertation	P	MSc
Display programming skills to be used in estimations of models with big data	P	PGDip, MSc
Exhibit Interpersonal and generic skills, such as communication, literacy, numeracy, IT	T	PGCert, PGDip, MSc

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

Programme structure

Full-time

This Master's Degree programme is studied full-time over one academic year, consisting of 180 credits at FHEQ level 7*. All modules are semester based and worth 15 credits with the exception of project, practice based and dissertation modules.
Possible exit awards include:
- Postgraduate Diploma (120 credits)
- Postgraduate Certificate (60 credits)
*some programmes may contain up to 30 credits at FHEQ level 6.

Programme Adjustments (if applicable)

N/A

Modules

Full-time

Year 1 (full-time) - FHEQ Levels 6 and 7

Module code	Module title	Status	Credits	Semester
ECOM020	MICROECONOMICS	Compulsory	15	1
ECOM021	MACROECONOMICS	Compulsory	15	1
ECOM027	RESEARCH METHODS	Compulsory	60	Year-long
ECOM031	FINANCIAL ECONOMETRICS	Optional	15	2
ECOM042	ECONOMETRICS 1	Compulsory	15	1
MAT3051	MATHEMATICS OF DATA SCIENCE	Optional	15	2
ECOM077	ADVANCED QUANTITATIVE METHODS IN ECONOMICS	Compulsory	15	1
ECOM075	MACHINE LEARNING METHODS AND BIG DATA	Compulsory	15	2
ECOM076	APPLICATIONS OF ECONOMETRICS TO BIG DATA	Compulsory	15	2
ECOM071	THEORY AND APPLICATIONS IN FINANCE	Optional	15	2
ECOM047	ADVANCED MACROECONOMICS	Optional	15	2
ECOM048	ADVANCED MICROECONOMICS	Optional	15	2
MATM063	PRINCIPLES OF DATA SCIENCE	Optional	15	2

Module Selection for Year 1 (full-time) - FHEQ Levels 6 and 7

Two from the list of optional modules

Opportunities for placements / work related learning / collaborative activity

Associate Tutor(s) / Guest Speakers / Visiting Academics	N
Professional Training Year (PTY)	N
Placement(s) (study or work that are not part of PTY)	N
Clinical Placement(s) (that are not part of the PTY scheme)	N
Study exchange (Level 5)	N
Dual degree	N

Quality assurance

The Regulations and Codes of Practice for taught programmes can be found at:

https://www.surrey.ac.uk/quality-enhancement-standards

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2023/4 academic year.